Wireless Sensor Communication Research Articles

Quantum walks-based simple authenticated quantum cryptography protocols for secure wireless sensor networks

Wireless sensor networks (WSNs) play a crucial role in various applications, ranging from environmental monitoring to industrial automation that require high levels of security. With the development of quantum technologies, many security mechanisms may be hacked due to the promising capabilities of quantum computation. To address this challenge, quantum protocols have emerged as a promising solution for enhancing the security of wireless sensor communications. One of the common types of quantum protocols is quantum key distribution (QKD) protocols, which are investigated to allow two participants with fully quantum capabilities to share a random secret key, while semi-quantum key distribution (SQKD) protocols are designed to perform the same task using fewer quantum resources to make quantum communications more realizable and practical. Quantum walk (QW) plays an essential role in quantum computing, which is a universal quantum computational paradigm. In this work, we utilize the advantages of QW to design three authenticated quantum cryptographic protocols to establish secure channels for data transmission between sensor nodes: the first one is authenticated quantum key distribution (AQKD), the second one is authenticated semi-quantum key distribution (ASQKD) with one of the two participants having limited quantum capabilities, and the last one is ASQKD but both legitimate users possess limited quantum resources. The advantages of the proposed protocols are that the partners can exchange several different keys with the same exchanged qubits, and the presented protocols depend on a one-way quantum communication channel. In contrast, all previously designed SQKD protocols rely on two-way quantum communication. Security analyses prove that the presented protocols are secure against various well-known attacks and highly efficient. The utilization of the presented protocols in wireless sensor communications opens up new avenues for secure and trustworthy data transmission, enabling the deployment of resilient WSNs in critical applications. This work also paves the way for future exploration of quantum-based security protocols and their integration into WSNs for enhanced data protection.

Metaheuristics Techniques for Cluster Head Selection in WSN: A Survey

In recent years, Wireless sensor communication is growing expeditiously on the capability to gather information, communicate and transmit data effectively. Clustering is the main objective of improving the network lifespan in Wireless sensor network. It includes selecting the cluster head for each cluster in addition to grouping the nodes into clusters. The cluster head gathers data from the normal nodes in the cluster, and the gathered information is then transmitted to the base station. However, there are many reasons in effect opposing unsteady cluster head selection and dead nodes. The technique for selecting a cluster head takes into factors to consider including residual energy, neighbors’ nodes, and the distance between the base station to the regular nodes. In this study, we thoroughly investigated by number of methods of selecting a cluster head and constructing a cluster. Additionally, a quick performance assessment of the techniques' performance is given together with the methods' criteria, advantages, and future directions.

Geometric formulations on wireless sensors based spatial protocol for intrusion detection using factor graphs

Restriction on intrusions is one of the foremost aspects of security to conserve the resources in a wireless network. The perimeter of the shadowing zone where in sensing and connectivity are simultaneously changing had to be estimated to prevent intruders. So the proposed work estimates a relationship between the data transmissions and computational time to find the trust factor of channels using factor graphs. Subsequently, estimating the Value of Information (VoI), contention time, and topological significance based on sensing power to alleviate blind spots had been observed to identify intrusions. Factor graph-based routing scenarios capable of handling channel uncertainties in time-triggered wireless sensor communication are indicated with edges and their factors. The process of local interactions with edges provides inference of intrusions to determine global solutions to preserve the network and its data transfer.

Ring slot CP antenna for the hybrid electromagnetic solar energy harvesting and IoT application

The research proposed a compact antenna integrated with dual-function solar cells to optimize internet of things (IoT) communication devices and energy harvesting. The use of integrated solar cells with electromagnetic elements as antennas and energy-gathering in a design is a solution for wireless communication sensors and simultaneously electromagnetic and solar energy harvesting. Radiation performance testing of solar cell antennas and optical experiments were carried out to test the ability of solar energy collection. A double feed ring slot circular polarization (CP) antenna coplanar antenna with a configuration has highly sensitive to vertical and horizontal waves. It is to accommodate the impact of circular polarization wave and solar cell distortion on antenna performance. This technology promises green communications, renewable energy, and environmental protection to combine wireless communication and green battery components. The study presents the performance and design results of a double line-feed microstrip antenna circuit connected with CP antenna on the S-band for IoT communication by accommodating electromagnetic energy transmission. The importance of adopting an integrated radio frequency (RF) solar energy harvesting strategy rather than a single source method makes this research very significant in its novelty by optimizing the analysis of multiple signal access in IoT communications.

ESPAR array design for the UHF RFID wireless sensor communication system

SummaryIn this paper, in order to improve the received signal strength (RSS) and signal quality, three arrays of electronically steerable parasitic array radiator (ESPAR) antennas are suggested for the ultra‐high frequency (UHF) radio frequency identification (RFID) communication and sensing system applications. Instead of the single antenna, the array antennas have recently been widely used in many communication systems because of their peak gains, better radiation patterns, and higher radiation efficiency. Also, there are some important issues to use the antenna array like high data rates in wireless communication systems and to better understand the many targets or sensors. In this article, a wireless sensor network (WSN) is being investigated to overcome multipath fading and interference by antenna nulling technology that can be achieved through beam control ESPAR array antennas. The proposed ESPAR array antennas exhibit higher gains like 9.63, 10.2, and 12 dBi and proper radiation patterns from one array to another. Moreover, we investigate the mutual coupling effect on the performance of array antennas with different spacing (0.5λ, 0.75λ, λ) and configurations. It is found that the worst mutual coupling reduced by −28 to −34 dB for 2 × 2 array, −3 to −43 dB for 2 × 3 array, and finally −42 dB to −51 dB due to the antenna spacing from 0.5λ to λ. Thus, these suggested antennas could effectively be applied in the WSN communication systems, internet of things (IoT) networks, and massive wireless and backscatter communication systems.

Design of a Compact ISM-band Microstrip Slot Antenna for Wireless Sensor Nodes

Objective: To enhance the design and implementation of microstrip antenna for wireless Sensor Networks (WSN) in real-time applications Methods: This study uses radio communication to connect end nodes and forms a multihop self-organizing network with a dynamic topology. Also, the antenna is fabricated from low-cost FR-4 printed circuit board (PCB) material. The designed rectangular patch antenna operates in the industrial, scientific, and medical (ISM) frequency band of 2.45 GHz, and HFSS software analyzer is used to authenticate the proposed work. Findings: The designed antenna finds an extensive use in short-range wireless sensor networks, the proposed antenna reduces the return loss from 10% - 13 % and almost 15% improvement in radiation compared with K. D. Xu (2018) and E. Zhang (2020). Novelty: A novel short range, low power, and well directional microstrip patch antenna are designed to improve the wireless Sensor communication applications operating at 2.4 GHz and 5.3 GHz frequencies. The presented approach is simple to operate, cost-effective, energy-efficient, and has optimum return loss performance (please refer Table 2) when compared to the existing approaches. Keywords: Microstrip antenna; Compact; HFSS; Wireless Sensor Network; dual frequency

Enhanced extremely weak-field energy harvesting via magnetic flux and stress concentration effects in ferromagnetic/ferroelectric composite

In this work, we report an enhanced magneto-mechano-electric (MME) coupling in Ni/Pb(Zr,Ti)O3 (PZT) ceramic composited ladder-type cantilever attached with a tip mass of NdFeB magnet, which simultaneously exhibits the magnetic flux concentration effect and the stress concentration effect, and therefore, it shows an enhanced extremely weak-field (EWF) coupling ability. Investigations show that the proposed MME energy harvester (EH) can generate an output power density of 7.16 μW Hz−1 Oe−2 cm−3, which is the highest value compared to the state of the art MME energy harvesters. Under an EWF of even as low as Hac = 0.1 Oe (about half level of the geomagnetic field), the proposed MME-EH can still produce a peak–peak output power of 23.5 μW, which is enough power to light up 4 LEDs in real time. Furthermore, it can drive a wireless sensor communication system in real time under a weak Hac = 0.75 Oe excitation, demonstrating it has potential to serve as a micro-energy source of wireless sensor networks in EWF circumstance. This work is not only beneficial but has also inspired future multi-function-integrated material and smart electronic device designs in Internet of Things in EWF circumstance.

Research on IEEE 802.11 OFDM Packet Detection Algorithms for Household Wireless Sensor Communication

Millions of smart home devices equipped with wireless sensors have gradually entered people’s homes and improved the quality of life. Wireless communication with sensors is crucial for remote automatic control of smart devices. Packet detection is one of the key technologies in wireless communication systems and faces the challenges of detection accuracy and power consumption. In households, WiFi devices are widely deployed. Therefore, we focus on IEEE 802.11 OFDM packet detection algorithms for household wireless sensor communication. We first introduce four packet detection algorithms and verify their feasibility by simulation experiments. Then, we identify two important factors that affect detection accuracy and provide suggestions for algorithm improvement. Further, we compare and discuss the performance of the four algorithms from three dimensions in detail. The results show that each algorithm has its own advantages, and the auto-correlation algorithm has the best overall performance. Finally, we point out the open challenges and future research directions in this field.

Разработка алгоритма повышения эффективности протокола маршрутизации С-LEACH

In the process of studying wireless sensor network protocols and communication mechanisms, the extension of network service life and minimization of node power consumption have become important indicators. In order to reduce the energy consumption caused by communication in a wireless sensor network, improve network scalability and extend the network lifecycle, it is important to intelligently connect network nodes using a certain clustering algorithm. The paper proposes an improved routing protocol for wireless sensors with low power consumption LEACH, based on data aggregation (C-LEACH). The Kalman filter algorithm was used to solve the problem of data accuracy on cluster member nodes. The principle of operation of the Kalman filter is explained by the example of the noise signal of the sensor. The above data modification model can be performed continuously to achieve the optimal evaluation and filtering effect. Thus, the volume of data sent by the node is reduced. Experimental results have shown that the proposed LEACH protocol based on data fusion (C-LEACH) effectively reduces data redundancy, reduces the power consumption of sensor nodes and prolongs the life cycle of wireless sensor networks compared to the traditional LEACH algorithm, significantly improves network integrity.

Deep Reinforcement Learning-Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications

The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficiency of the upcoming beyond fifth generation network (B5G), especially for support the wireless sensor communications in Internet of things (IoT) system. However, how to realize intelligent frequency, time, and energy resource allocation to support better performances is an important problem to be solved. In this paper, we study joint spectrum, energy, and time resource management for the EH-CR-NOMA IoT systems. Our goal is to minimize the number of data packets losses for all secondary sensing users (SSU), while satisfying the constraints on the maximum charging battery capacity, maximum transmitting power, maximum buffer capacity, and minimum data rate of primary users (PU) and SSUs. Due to the non-convexity of this optimization problem and the stochastic nature of the wireless environment, we propose a distributed multidimensional resource management algorithm based on deep reinforcement learning (DRL). Considering the continuity of the resources to be managed, the deep deterministic policy gradient (DDPG) algorithm is adopted, based on which each agent (SSU) can manage its own multidimensional resources without collaboration. In addition, a simplified but practical action adjuster (AA) is introduced for improving the training efficiency and battery performance protection. The provided results show that the convergence speed of the proposed algorithm is about 4 times faster than that of DDPG, and the average number of packet losses (ANPL) is about 8 times lower than that of the greedy algorithm.

Wireless-Sensor Communication Based Wireless-Charging Coil Positioning System for UAVs With Maximum Power Point Tracking

Drone is a piece of power-hungry equipment whose battery drains within the first few minutes of its takeoff, and the user has to physically change the battery to a fully charged one. Implementation of wireless power transfer (WPT) in unmanned aerial vehicles has started becoming a reality. However, the technology is prone to many problems, especially misalignment between transmitter and receiver coils. The WPT system faces a sudden decline in power transfer with few millimeters of lateral misalignment between the transmitter and the receiver coil. The proposed sensor-based tracking system creates a two-way communication between the transmitter and the receiver coil systems for exchanging maximum power point information. The transmitter coil is adjusted directly beneath the receiver coil for maximum power transfer. The proposed WPT charging system reduces the misalignment issue by a significant factor and achieves maximum coupling efficiency. At 10 mm vertical distance, 0 mm lateral displacement between transmitter and receiver coils, the system achieved 91.3% power transfer efficiency by wirelessly receiving 70 W of power. The system offers practical, autonomous charging use cases in surveying, agriculture, and mapping applications.

CUCKOO-ANN Based Novel Energy-Efficient Optimization Technique for IoT Sensor Node Modelling

Wireless sensor networks (WSNs) based on the Internet of Things (IoT) are now one of the most prominent wireless sensor communication technologies. WSNs are often developed for particular applications such as monitoring or tracking in either indoor or outdoor environments, where battery power is a critical consideration. To overcome this issue, several routing approaches have been presented in recent years. Nonetheless, the extension of the network lifetime in light of the sensor capabilities remains an open subject. In this research, a CUCKOO-ANN based optimization technique is applied to obtain a more efficient and dependable energy efficient solution in IoT-WSN. The proposed method uses time constraints to minimize the distance between sources and sink with the objective of a low-cost path. Using the property of CUCKOO method for solving nonlinear problem and utilizing the ANN parallel handling capability, this method is formulated. The resented model holds significant promise since it reduces average execution time, has a high potential for enhancing data centre energy efficiency, and can effectively meet customer service level agreements. By considering the mobility of the nodes, the technique outperformed with an efficiency of 98% compared with other methods. The MATLAB software is used to simulate the proposed model.

Potential Energy Efficient Data Fusion Model for Wireless Sensor Networks

Wireless sensor networks have made a significant contribution to wireless sensor communication system based on resource constraints and limited computational sensors. Over the last decade, several focused research efforts have been made to investigate and provide solutions to problems relating to the energy efficiency data fusion aggregation in Wireless sensor networks. However, the problem of designing routes that are energy efficient has not been resolved. It is rather a tough effort to guarantee that the lifespan of a sensor is prolonged for a longer period because of the restricted computational capabilities of sensors, which are often coupled with energy constraints. The findings of this work present an enhanced energy-efficient technique for communication in sensor networks which consists of three distinct innovative frameworks. The suggested framework known as Data Fusion with Potential Energy Efficiency (DFWPEE) is responsible for the optimization of energy. The proposed work reduces energy consumption by using probabilistic methods and clustering. During the data fusion process, the Multiple Zone Data Fusion (MZDF) architecture uses a globular topology that helps with load balancing. The strategy presents an innovative routing approach that is used to aid in the performance of energy efficient routing in large-scale wireless sensor networks. By introducing the idea of routing agents, the framework for the Tree-Based Fusion Technique (TBFT), as suggested, comes up with an innovative method for dynamic reconfiguration. The plan enables the system to determine which sensor has a higher rate of energy dissipation and then immediately transfers the job of data fusion to a node that is more energy efficient. This threshold-based technique enables a sensor to perform both the role of a cluster head and the function of a member node. The node behaves as a cluster head until it achieves its threshold remnant energy and functions as a member node after it passes the threshold residual energy. Both of these roles may be played simultaneously. The mathematical modeling was done using the conventional radio energy model which improved the dependability of attained results. The proposed system delivers enhanced energy efficient communication performance when measured against existing implemented standards for energy efficient schemes. The enhanced technique uses nearly half as much energy as LEACH while focusing on reducing the overall time taken for the process to complete leading to enhanced performance.

VLSI Based Architecture in ECG Monitoring for Adaptive Power Management In Wireless Bio Signal Acquisition Network

For the diagnosis and elimination of cardiovascular diseases, the ECG system has evolved as smarter healthcare professionals. As almost all of these networks are battery-operated, the whole device’s total life is greatly shortened by self-centred communication connections. This paper will present a power control technique and the accompanying VLSI design to improve the Asic ECG heart monitor’s lifespan powered by the battery. The suggested power control strategy dynamically adjusts between two transmission modes, i.e. high performance / lower energy modes, available for a device’s energy level. Because localized storage is energy, for true monitoring of QRS complexity and breathing rates assessment, a streamlined methodology focusing on slopes improvement with runtime adaptive thresholding is intended to guarantee maximum energy usage throughout limited energy level. The required communication mode is chosen based mostly on batteries and pulse rate consistency, which essentially fulfils the Wireless Body Sensor Communication network objective. Collecting appropriate ECG collections from a single customer and enhancing the longevity of the device. Response and efficiency are evaluated for the proposed method The ultra - low - power signal generator with a relaxing scope range of 1-3 m will be built to retain a bigger battery. Any transmitter and receiver for remote private communication standards have been established lately. It is not the best option for ultra-low power WBAN implementations. The Spartan 6 FPGA design has been introduced with a peak clock frequency of 269 MHz with an energy demand of 0.3mW, specially designed for actual ECG measurement techniques.

Distributed filtering stochastic parameter learning algorithm for discrete-time random nonlinear systems with delay

Distributed filtering algorithm for a discrete time random nonlinear stochastic systems associated with state delay for the distributed wireless communication sensors are discussed in this paper. Stochastic Parameter Learning Algorithm (SPLA) is tend to aim at obtaining a collection of stochastic filter parameters in a finite limited time horizon, that minimize the traces of the upper limits which is permitted to reduce the error variance matrices of the concerned stochastic filter system’s states and delay measurements. Filter gain values of the filter derived by the determination of Riccati type difference equations, estimates systems states with delay. Two different filter rules are taken into account for the SPLA discrete time random nonlinear systems with steady state space equations model. Zero mean distinct covariance matrix along with the constructive state values and constant time delay are focused in compatible dimensions. The variance of the projected systems predicted noise and the actual estimated noise are validated through numerical examples.

Construction of 3D Soil Moisture Maps in Agricultural Fields by Using Wireless Sensor Communication

Over-irrigation without considering the soil property reduce the product yield and variety in many agricultural areas. In this study, it is aimed to produce a more useful, and user-friendly 3D soil moisture detection system by using wireless communication across the agricultural areas. The deficiencies of agricultural land can be eliminated in terms of irrigation, product variety, and product yield. 3D moisture information obtained from the soil can be transferred to a database system and the farmers can use this system to cultivate across the correct fields. A capacitive soil moisture sensor is deployed as a sensor unit. Each sensor unit with its electronics is placed in a PVC pipe with a specific length. This PVC pipe is placed vertically in the soil with sensor electrodes contacting the soil. Moisture measurements are carried out across the agricultural area. The system provides 3D moisture maps of the soil at fixed depths. Each 3D map represents a sub-surface moisture layer. The sensor units are calibrated by measuring the moisture in the water, corresponding to %100 moisture in the soil, and the moisture in dry air, corresponding to %0 moisture in the soil. A percentage moisture determination formula is developed between these two extreme levels for each sensor unit. Hence the benefit of the results will be the knowledge of % moisture values in-depth profile of the agricultural areas. Farmers will have comprehensive and real-time information about moisture data and this data will help them to grow better crops.

Modified constant modulus algorithm based on bat algorithm

In this work, modified constant modulus algorithm based on bat algorithm is proposed for wireless sensor communications systems. The bat algorithm is a swarm intelligence optimization algorithm, which mainly used to solve optimization problems. The proposed algorithm focused on modified constant modulus algorithm, which is also applicable to the constant modulus algorithm. The error function of blind equalization algorithm is used as the evaluation function of the bat algorithm, and then the initial value of the weight vector is calculated adaptively by the bat algorithm. Theoretical analysis is provided to illustrate that the proposed algorithm has a faster convergence speed than the original one and is suitable for almost all blind channel equalization algorithms. The simulation results support the newly proposed improved algorithm. The proposed algorithm could be applied to some more complex wireless channel environments to improve the reception performance of sensor communication systems.

NRSM: node redeployment shrewd mechanism for wireless sensor network

Despite numerous advantages, the challenges for wireless sensor communication always remains open due to which a continuous effort is being applied to tackle the unavoidable conditions regarding wireless network coverage. Somehow, the uncouth deployment of the sensor nodes is making the tribulation queue longer day by day which eventually has great impact over sensor coverage range. To address the issues related with network coverage and uncouth energy wastage, a sensor node redeployment-based shrewd mechanism (NRSM) has been proposed where new intended positions for sensor node are rummaged out in the coverage area. The proposed algorithm operates in two phases; in first phase it locates the intended node positions through Dissimilitude Enhancement Scheme (DES) and moves the node to new position. While second phase is called a Depuration, when the moving distance between initial and intended node position is shrewdly reduced. Further, different variation factors of NRSM such as loudness, pulse emission rate, maximum frequency, and sensing radius have been explored and related optimized parameters are identified. The performance metric has been meticulously analyzed through simulation rounds in Matlab and compared with state of art algorithms like Fruit Fly Optimization Algorithm (FOA), Jenga-inspired optimization algorithm (JOA) and Bacterial Foraging Algorithm (BFA) in terms of mean coverage range, computation time, standard deviation and network energy diminution. The performance metrics vouches the effectiveness of the proposed algorithm as compared to the FOA, JOA and BFA.

The network of telecommunications cross‐layer cooperation control of wireless sensor communication network applied in smart distribution grid

SummaryWith the rapid development of artificial intelligence, the intelligent distribution network can effectively improve the overall power supply quality of the distribution system. The designed distributed power has been able to achieve an optimal operation of grid connection, while the high‐speed operation of distribution equipment can achieve effective interaction with users. At present, intelligent distribution network is widely studied and applied in power industry because of its advantages of high efficiency energy and environmental protection. Because of its unique characteristics, such as low cost and fast speed, wireless sensor network is cleverly applied in intelligent distribution network. However, wireless sensor network has some defects in energy utilization due to its large range and too many nodes. This paper presents a cross‐layer cooperative control model, which can control the real time and reliability of network power data communication through stack protocol layer. This method can learn the weight value adaptively by training the influence relationship between the parameters of each protocol layer and achieve real‐time and reliable data communication by adjusting the policy and parameters of each layer in real time. This method takes the parameters of each wireless sensor node as the unit to establish the influence relationship between each other so as to realize the connection between each node of wireless sensor network and then to control the wireless sensor network as a whole to ensure the real‐time reliability of data communication in intelligent distribution network. In this paper, a lot of simulation experiments have been done, and the results show that the proposed cross‐layer cooperative control model can control the whole wireless sensor network to achieve efficient data transmission capacity of intelligent distribution wireless sensor network.

Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges.

In recent years there has been an increasing need for miniature, low-cost, commercially accessible, and user-friendly sensor solutions for wireless body area networks (WBAN), which has led to the adoption of new physical communication interfaces providing distinctive advantages over traditional wireless technologies. Ultra-wideband (UWB) and intrabody communication (IBC) have been the subject of intensive research in recent years due to their promising characteristics as means for short-range, low-power, and low-data-rate wireless interfaces for interconnection of various sensors and devices placed on, inside, or in the close vicinity of the human body. The need for safe and standardized solutions has resulted in the development of two relevant standards, IEEE 802.15.4 (for UWB) and IEEE 802.15.6 (for UWB and IBC), respectively. This paper presents an in-depth overview of recent studies and advances in the field of application of UWB and IBC technologies for wireless body sensor communication systems.